Abstract
The Microwave Interferometric Radiometer with Aperture Synthesis (MIRAS) is the payload of the Soil Moisture and Ocean Salinity (SMOS) satellite mission led by the European Space Agency. Although the MIRAS operates at the protected L-band, it is perturbed by radio frequency interferences (RFIs) that contaminate the acquired remote sensing data and further deteriorate the total performance of SMOS mission. Accurate location information of these sources is crucial for switching off illegal RFI emitters or mitigating RFI impacts from contaminated data. This article addresses the localization of SMOS RFI sources from a perspective of sparse signal reconstruction (SSR), which exploits the sparsity of RFI sources in the spatial domain. Such an SSR strategy possesses superior (at least comparable) performances over existing RFI localization methods [e.g., discrete Fourier transformation (DFT) inversion and subspace-based direction-of-arrival (DOA) estimation] using only SMOS measurements and even under situations in the presence of data missing due to correlator failures.
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